On Mon, Apr 9, 2012 at 10:52 PM, Travis Oliphant wrote:
> Hey all,
>
> I've been waiting for Mark Wiebe to arrive in Austin where he will spend
> several weeks, but I also know that masked arrays will be only one of the
> things he and I are hoping to make head-way on while he is in Austin.
> Nev
Hey all,
I've been waiting for Mark Wiebe to arrive in Austin where he will spend
several weeks, but I also know that masked arrays will be only one of the
things he and I are hoping to make head-way on while he is in Austin.
Nevertheless, we need to make progress on the masked array discus
On Mon, Apr 9, 2012 at 12:22 PM, Benjamin Root wrote:
>
>
> On Mon, Apr 9, 2012 at 12:14 PM, Jonathan T. Niehof wrote:
>
>> On 04/06/2012 06:54 AM, Benjamin Root wrote:
>>
>> > Take a peek at how np.gradient() does it. It creates a list of None with
>> > a length equal to the number of dimensions
On Apr 9, 2012, at 7:21 PM, Nathaniel Smith wrote:
> ...isn't this an operation that will be performed once per compiled function?
> Is the overhead of the easy, robust method (calling ctypes.cast) actually
> measurable as compared to, you know, running an optimizing compiler?
>
>
Yes, there
...isn't this an operation that will be performed once per compiled
function? Is the overhead of the easy, robust method (calling ctypes.cast)
actually measurable as compared to, you know, running an optimizing
compiler?
I mean, I doubt there'd be any real problem with adding this extra API to
num
Hi all,
Some of you are aware of Numba. Numba allows you to create the equivalent of
C-function's dynamically from Python. One purpose of this system is to allow
NumPy to take these functions and use them in operations like ufuncs,
generalized ufuncs, file-reading, fancy-indexing, and so f
On 4/3/12 4:18 PM, Ralf Gommers wrote:
> Here some first impressions.
>
> The good:
> - It's responsive!
> - It remembers my preferences (view type, # of issues per page, etc.)
> - Editing multiple issues with the command window is easy.
> - Search and filter functionality is powerful
>
> The bad:
On 12-04-09 11:27 AM, Chris Barker wrote:
>
>
http://www.eos.ubc.ca/research/clouds/software/pythonlibs/num_util/num_util_release2/Readme.html
>
>
> also pretty old.
>
> So I'd go with the actively maintained on -- or Cython -- what I can
> tell you is that Cython is being very widely used in t
On 04/08/2012 08:25 PM, Holger Herrlich wrote:
>
> That all sounds like no option -- sad.
> Cython is no solution cause, all I want is to leave Python Syntax in
> favor for strong OOP design patterns.
I'm sorry, I'm trying and trying to make heads and tails of this
paragraph, but I don't manage t
> That all sounds like no option -- sad.
> Cython is no solution cause, all I want is to leave Python Syntax in
> favor for strong OOP design patterns.
What about ctypes?
For straight numerical work where sometimes all one needs to hand across the
python-to-C/C++/Fortran boundary is a pointer to
2012/4/9 Hänel Nikolaus Valentin :
http://www.eos.ubc.ca/research/clouds/software/pythonlibs/num_util/num_util_release2/Readme.html
>>
>> that looks like it hasn't been updated since 2006 -- I"d say that
>> makes it a non-starter
>
> Yeah, thats what I thought... Until I found it in several produc
Hi Chris,
thanks for your answer.
* Chris Barker [2012-04-09]:
> 2012/4/8 Hänel Nikolaus Valentin >:
> http://www.eos.ubc.ca/research/clouds/software/pythonlibs/num_util/num_util_release2/Readme.html
>
> that looks like it hasn't been updated since 2006 -- I"d say that
> makes it a non-starter
2012/4/8 Hänel Nikolaus Valentin :
http://www.eos.ubc.ca/research/clouds/software/pythonlibs/num_util/num_util_release2/Readme.html
that looks like it hasn't been updated since 2006 -- I"d say that
makes it a non-starter
The new numpy-boost project looks promising, though.
> which was also menti
On Mon, Apr 9, 2012 at 12:14 PM, Jonathan T. Niehof wrote:
> On 04/06/2012 06:54 AM, Benjamin Root wrote:
>
> > Take a peek at how np.gradient() does it. It creates a list of None with
> > a length equal to the number of dimensions, and then inserts a slice
> > object in the appropriate spot in th
On 04/06/2012 06:54 AM, Benjamin Root wrote:
> Take a peek at how np.gradient() does it. It creates a list of None with
> a length equal to the number of dimensions, and then inserts a slice
> object in the appropriate spot in the list.
List of slice(None), correct? At least that's what I see in
Hello,
Is there NpyAccessLib documentation available?
I need to use DLLImport for a C# IronPython DLR app and am not sure which
methods to include.
Thank you.
Regards,
William Johnston
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On Mon, Apr 9, 2012 at 10:53 AM, Michael McNeil Forbes
wrote:
> It seems like functools.partial is the appropriate tool to use here
> which means I will have to deal with the
functools was added in Python 2.5, and so far numpy is still trying to
maintain 2.4 compatibility. (Not that this is parti
On 8 Apr 2012, at 12:09 PM, Ralf Gommers wrote:
> That looks like a useful enhancement. Integrating in the existing
> vectorize class should be the way to go.
Okay. I will push forward. I would also like to add support for
"freezing" (or "excluding") certain arguments from the vectorization.
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